ALBERT

Description: This study investigates the influence of microstructure on the effective ionic and electrical conductivities of Ni-YSZ (yttria-stabilized zirconia) anodes. Fine, medium, and coarse microstructures are exposed to redox cycling at 950 °C. FIB (focused ion beam)-tomography and image analysis are used to quantify the effective (connected) volume fraction (Φeff), constriction factor (β), and tortuosity (τ). The effective conductivity (σeff) is described as the product of intrinsic conductivity (σ0) and the so-called microstructure-factor (M): σeff = σ0*M. Two different methods are used to evaluate the M-factor: (1) by prediction using a recently established relationship, Mpred = εβ0.36/τ5.17, and (2) by numerical simulation that provides conductivity, from which the simulated M-factor can be deduced (Msim). Both methods give complementary and consistent information about the effective transport properties and the redox degradation mechanism. The initial microstructure has a strong influence on effective conductivities and their degradation. Finer anodes have higher initial conductivities but undergo more intensive Ni coarsening. Coarser anodes have a more stable Ni phase but exhibit lower YSZ stability due to lower sintering activity. Consequently, in order to improve redox stability, it is proposed to use mixtures of fine and coarse powders in different proportions for functional anode and current collector layers.

Description: In the effort to combat global warming, renewable energies play a key role. However, most efforts are still focused on the electricity market, so renewables remain underrepresented in the heat market. Biomethane derived from biogas is an intriguing option for using renewable energy to generate heat in residential homes. However, biomethane comes at a significantly higher cost than natural gas, meaning providers have to ask a price premium from consumers. Determining a pricing strategy is thus of crucial importance. Besides cost, providers have to consider consumers’ willingness-to-pay (WTP) for the product. We propose that they could draw on existing research on WTP for green electricity, albeit with some important modifications and scarce research on biomethane. To explore this proposition, we performed a first-of-its-kind analysis of providers’ pricing strategies for biomethane, using both providers’ published data and data provided in response to e-mail queries. Based on the features and prices of 165 biomethane-based gas products for private households in Germany, we find that features that could, according to existing research, elicit a higher WTP are not priced accordingly. As the consumer market for biomethane is still in its early development, our results suggest opportunities for providers to ask higher prices for certain biomethane-based gas products.

Description: The cloud index is a key parameter of the Heliosat method. This method is widely used to calculate solar irradiance on the Earth’s surface from Meteosat visible channel images. Moreover, cloud index images are the basis of short-term forecasting of solar irradiance and photovoltaic power production. For this purpose, cloud motion vectors are derived from consecutive images, and the motion of clouds is extrapolated to obtain forecasted cloud index images. The cloud index calculation is restricted to the daylight hours, as long as SEVIRI HR-VIS images are used. Hence, this forecast method cannot be used before sunrise. In this paper, a method is introduced that can be utilized a few hours before sunrise. The cloud information is gained from the brightness temperature difference (BTD) of the 10.8 µm and 3.9 µm SEVIRI infrared channels. A statistical relation is developed to assign a cloud index value to either the BTD or the brightness temperature T10:8, depending on the cloud class to which the pixel belongs (fog and low stratus, clouds with temperatures less than 232 K, other clouds). Images are composed of regular HR-VIS cloud index values that are used to the east of the terminator and of nighttime BTD-derived cloud index values used to the west of the terminator, where the Sun has not yet risen. The motion vector algorithm is applied to the images and delivers a forecast of irradiance at sunrise and in the morning. The forecasted irradiance is validated with ground measurements of global horizontal irradiance, and the advantage of the new approach is shown. The RMSE of forecasted irradiance based on the presented nighttime cloud index for the morning hours is between 3 and 70 W/m2, depending on the time of day. This is an improvement against the previous precision range of the forecast based on the daytime cloud index between 70 and 85 W/m2.

Description: Due to an oversight by the authors, the following correction is necessary in this publication [1].[...]

Description: As specifically designed platforms are still unavailable at this point in time, lava flows are usually monitored remotely with the use of meteorological satellites. Generally, meteorological satellites have a low spatial resolution, which leads to uncertain results. This paper presents the first long term satellite monitoring of active lava flows on Stromboli volcano (August–November 2014) at high spatial resolution (160 m) and relatively high temporal resolution (~3 days). These data were retrieved by the small satellite Technology Experiment Carrier-1 (TET-1), which was developed and built by the German Aerospace Center (DLR). The satellite instrument is dedicated to high temperature event monitoring. The satellite observations were accompanied by field observations conducted by thermal cameras. These provided short time lava flow dynamics and validation for satellite data. TET-1 retrieved 27 datasets over Stromboli during its effusive activity. Using the radiant density approach, TET-1 data were used to calibrate the MODVOLC data and estimate the time averaged lava discharge rate. With a mean output rate of 0.87 m3/s during the three-month-long eruption, we estimate the total erupted volume to be 7.4 × 106 m3.

Description: This paper aims at assessing the accuracy of different solar forecasting methods in the case of an insular context. Two sites of La Réunion Island, Le Tampon and Saint-Pierre, are chosen to do the benchmarking exercise. Réunion Island is a tropical island with a complex orography where cloud processes are mainly governed by local dynamics. As a consequence, Réunion Island exhibits numerous micro-climates. The two aforementioned sites are quite representative of the challenging character of solar forecasting in the case of a tropical island with complex orography. Hence, although distant from only 10 km, these two sites exhibit very different sky conditions. This work focuses on day-ahead and intra-day solar forecasting. Day-ahead solar forecasts are provided by the European Center for Medium-Range Weather Forecast (ECMWF). This organization maintains and runs the Numerical Weather Prediction (NWP) model named Integrated Forecast System (IFS). In this work, post-processing techniques are applied to refine the output of the IFS model for day-ahead forecasting. Statistical models like a recursive linear model or a nonlinear model such as an artificial neural network are used to produce the intra-day solar forecasts. It is shown that a combination of the IFS model and the neural network model further improves the accuracy of the forecasts.

Description: 3D microstructure-performance relationships in Ni-YSZ anodes for electrolyte-supported cells are investigated in terms of the correlation between the triple phase boundary (TPB) length and polarization resistance (Rpol). Three different Ni-YSZ anodes of varying microstructure are subjected to eight reduction-oxidation (redox) cycles at 950 °C. In general the TPB lengths correlate with anode performance. However, the quantitative results also show that there is no simplistic relationship between TPB and Rpol. The degradation mechanism strongly depends on the initial microstructure. Finer microstructures exhibit lower degradation rates of TPB and Rpol. In fine microstructures, TPB loss is found to be due to Ni coarsening, while in coarse microstructures reduction of active TPB results mainly from loss of YSZ percolation. The latter is attributed to weak bottlenecks associated with lower sintering activity of the coarse YSZ. The coarse anode suffers from complete loss of YSZ connectivity and associated drop of TPBactive by 93%. Surprisingly, this severe microstructure degradation did not lead to electrochemical failure. Mechanistic scenarios are discussed for different anode microstructures. These scenarios are based on a model for coupled charge transfer and transport, which allows using TPB and effective properties as input. The mechanistic scenarios describe the microstructure influence on current distributions, which explains the observed complex relationship between TPB lengths and anode performances. The observed loss of YSZ percolation in the coarse anode is not detrimental because the electrochemical activity is concentrated in a narrow active layer. The anode performance can be predicted reliably if the volume-averaged properties (TPBactive, effective ionic conductivity) are corrected for the so-called short-range effect, which is particularly important in cases with a narrow active layer.

Description: Sustainability, Vol. 10, Pages 2915: A Multi-Data Approach for Spatial Risk Assessment of Topsoil Compaction on Arable Sites Sustainability doi: 10.3390/su10082915 Authors: Sandra Ledermüller Marco Lorenz Joachim Brunotte Norbert Fröba Soil compaction is a human-induced threat which negatively affects soil functions and is highly dependent on site-specific soil conditions and land use patterns. Proper management techniques are indispensable for sustainable soil protection to ensure its function in the long term. A number of concepts exist to develop risk maps on the basis of soil inherent susceptibility to compaction at a given soil moisture level (mostly field capacity). However, the real soil conditions, e.g., current soil moisture content at the time of field work and the real machinery load, are not taken into account. To bridge this gap, we present a multi-data approach for qualitative risk assessment, which combines spatially and temporally explicit data on soil, soil moisture, and land use information. The contributing components integrate daily probability distribution, including inter- and intra-annual variations in land use and weather. We combined soil susceptibility to compaction and field work for the federal state of Lower Saxony per half-months and identified three clusters with more or less compaction risk for Lower Saxony. In spring, mainly manure spreading to maize and in autumn harvesting of maize and sugar beets are contributing to the yearly probability of compaction risk in top soils. With the presented approach risk areas can be identified. For the evaluation of the current compaction risks, farm specifications on machinery and timing of field work must also be taken into account.

Description: Materials, Vol. 11, Pages 1800: Hysteretic Photochromic Switching (HPS) in Doubly Doped GaN(Mg):Eu—A Summary of Recent Results Materials doi: 10.3390/ma11101800 Authors: Paul R. Edwards Kevin P. O’Donnell Akhilesh K. Singh Douglas Cameron Katharina Lorenz Mitsuo Yamaga Jacob H. Leach Menno J. Kappers Michal Boćkowski Europium is the most-studied and least-well-understood rare earth ion (REI) dopant in GaN. While attempting to increase the efficiency of red GaN light-emitting diodes (LEDs) by implanting Eu+ into p-type GaN templates, the Strathclyde University group, in collaboration with IST Lisbon and Unipress Warsaw, discovered hysteretic photochromic switching (HPS) in the photoluminescence spectrum of doubly doped GaN(Mg):Eu. Our recent work, summarised in this contribution, has used time-, temperature- and light-induced changes in the Eu intra-4f shell emission spectrum to deduce the microscopic nature of the Mg-Eu defects that form in this material. As well as shedding light on the Mg acceptor in GaN, we propose a possible role for these emission centres in quantum information and computing.

Description: Remote Sensing, Vol. 10, Pages 1366: Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring Remote Sensing doi: 10.3390/rs10091366 Authors: Moritz Kirsch Sandra Lorenz Robert Zimmermann Laura Tusa Robert Möckel Philip Hödl René Booysen Mahdi Khodadadzadeh Richard Gloaguen Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improves the reliability, safety, and efficiency of geological activities during exploration and mining monitoring. We describe an integrated workflow to produce a geometrically and spectrally accurate combination of a Structure-from-Motion Multi-View Stereo point cloud and hyperspectral data cubes in the visible to near-infrared (VNIR) and short-wave infrared (SWIR), as well as long-wave infrared (LWIR) ranges acquired by terrestrial and drone-borne imaging sensors. Vertical outcrops in a quarry in the Freiberg mining district, Saxony (Germany), featuring sulfide-rich hydrothermal zones in a granitoid host, are used to showcase the versatility of our approach. The image data are processed using spectroscopic and machine learning algorithms to generate meaningful 2.5D (i.e., surface) maps that are available to geologists on the ground just shortly after data acquisition. We validate the remote sensing data with thin section analysis and laboratory X-ray diffraction, as well as point spectroscopic data. The combination of ground- and drone-based photogrammetric and hyperspectral VNIR, SWIR, and LWIR imaging allows for safer and more efficient ground surveys, as well as a better, statistically sound sampling strategy for further structural, geochemical, and petrological investigations.